Machine Learning with Tensorflow

Nishant Shukla (Autor)

Buch | Softcover

325 Seiten

2017
Manning Publications (Verlag)
978-1-61729-387-0 (ISBN)

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Lots of diagrams, code examples, and exercises
Solves real-world problems with TensorFlow
Uses well-studied neural network architectures
Presents code that can be used for the readers' own applications

Being able to make near-real-time decisions is becoming increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you're just starting out in the data science field, how do you get started creating machine learning applications?

The answer is TensorFlow, a new open source machine learning library from Google. The TensorFlow library can take your high level designs and turn them into the low level mathematical operations required by machine learning algorithms. Google open-sourced their machine learning framework called TensorFlow in late 2015 under the Apache 2.0 license. Before that, it was used proprietarily by Google in its speech recognition, Search, Photos, and Gmail, among other applications. TensorFlow is one the most popular machine learning libraries.

Machine Learning with TensorFlow teaches readers about machine learning algorithms and how to implement solutions with TensorFlow. It starts with an overview of machine learning concepts and moves on to the essentials needed to begin using TensorFlow. Each chapter zooms into a prominent example of machine learning. Readers can cover them all to master the basics or skip around to cater to their needs.

By the end of this book, readers will be able to solve classification, clustering, regression, and prediction problems in the real world.

This book is for programmers who have some experience with Python and linear algebra concepts like vectors and matrices. No experience with machine learning is necessary.

Nishant Shukla is a computer vision researcher at UCLA, focusing on machine learning techniques with robotics. He has been a developer for Microsoft, Facebook, and Foursquare, and a machine learning engineer for SpaceX, as well as the author of the Haskell Data Analysis Cookbook.

An excellent introduction to the concepts of TensorFlow and various fitting techniques. Ken Fricklas

Excellent book for learning machine learning with Tensorflow. Ursin Stauss

Should be studied by every machine learning developer. William Wheeler

Erscheinungsdatum	01.04.2017
Verlagsort	New York
Sprache	englisch
Gewicht	468 g
Einbandart	kartoniert
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
	Mathematik / Informatik ► Informatik ► Netzwerke
	Mathematik / Informatik ► Informatik ► Software Entwicklung
	Informatik ► Theorie / Studium ► Algorithmen
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Schlagworte	Data Science • künstliche Intelligenz AI • Maschinelles Lernen • Python • Real Time
ISBN-10	1-61729-387-3 / 1617293873
ISBN-13	978-1-61729-387-0 / 9781617293870
Zustand	Neuware